OpenRaiser/Intern-Atlas huggingface dataset:
LinkedCT: A Linked Data Space for Clinical Trials
Venue: arXiv cs.DB 2009
Year: 2009

The Linked Clinical Trials (LinkedCT) project aims at publishing the first open semantic web data source for clinical trials data. The database exposed by LinkedCT is generated by (1) transforming existing data sources of clinical trials into RDF, and (2) discovering semantic links between the records in the trials data and several other data sources. In this paper, we discuss several challenges involved in these two steps and present the methodology used in LinkedCT to overcome these challenges. Our approach for semantic link discovery involves using state-of-the-art approximate string matching techniques combined with ontology-based semantic matching of the records, all performed in a declarative and easy-to-use framework. We present an evaluation of the performance of our proposed techniques in several link discovery scenarios in LinkedCT.
The Infinite Hierarchical Factor Regression Model
Venue: arXiv cs.LG 2009
Year: 2009

We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman's coalescent. We apply this model to two problems (factor analysis and factor regression) in gene-expression data analysis.
Deterministic Construction of Compressed Sensing Matrices using BCH Codes
Venue: arXiv cs.IT 2009
Year: 2009

In this paper we introduce deterministic $m\times n$ RIP fulfilling $\pm 1$ matrices of order $k$ such that $\frac{\log m}{\log k}\approx \frac{\log(\log_2 n)}{\log(\log_2 k)}$. The columns of these matrices are binary BCH code vectors that their zeros are replaced with -1 (excluding the normalization factor). The samples obtained by these matrices can be easily converted to the original sparse signal; more precisely, for the noiseless samples, the simple Matching Pursuit technique, even with less than the common computational complexity, exactly reconstructs the sparse signal. In addition, using Devore's binary matrices, we expand the binary scheme to matrices with $\{0,1,-1\}$ elements.
A Taxonomy of Collaboration in Online Information Seeking
Venue: arXiv cs.IR 2009
Year: 2009

People can help other people find information in networked information seeking environments. Recently, many such systems and algorithms have proliferated in industry and in academia. Unfortunately, it is difficult to compare the systems in meaningful ways because they often define collaboration in different ways. In this paper, we propose a model of possible kinds of collaboration, and illustrate it with examples from literature. The model contains four dimensions: intent, depth, concurrency and location. This model can be used to classify existing systems and to suggest possible opportunities for design in this space.
Toward Collaborative Information Seeking (CIS)
Venue: arXiv cs.IR 2009
Year: 2009

It is natural for humans to collaborate while dealing with complex problems. In this article I consider this process of collaboration in the context of information seeking. The study and discussion presented here are driven by two dissatisfactions: (1) the majority of IR systems today do not facilitate collaboration directly, and (2) the concept of collaboration itself is not well-understood. I begin by probing the notion of collaboration and propose a model that helps us understand the requirements for a successful collaboration. A model of a Collaborative Information Seeking (CIS) environment is then rendered based on an extended model of information seeking.
Localization dynamics in a binary two-dimensional cellular automaton: the Diffusion Rule
Venue: arXiv cs.FL 2009
Year: 2009

We study a two-dimensional cellular automaton (CA), called Diffusion Rule (DR), which exhibits diffusion-like dynamics of propagating patterns. In computational experiments we discover a wide range of mobile and stationary localizations (gliders, oscillators, glider guns, puffer trains, etc), analyze spatio-temporal dynamics of collisions between localizations, and discuss possible applications in unconventional computing.
Authentication Without Identification using Anonymous Credential System
Venue: arXiv cs.CR 2009
Year: 2009

Privacy and security are often intertwined. For example, identity theft is rampant because we have become accustomed to authentication by identification. To obtain some service, we provide enough information about our identity for an unscrupulous person to steal it (for example, we give our credit card number to Amazon.com). One of the consequences is that many people avoid e-commerce entirely due to privacy and security concerns. The solution is to perform authentication without identification. In fact, all on-line actions should be as anonymous as possible, for this is the only way to guarantee security for the overall system. A credential system is a system in which users can obtain credentials from organizations and demonstrate possession of these credentials. Such a system is anonymous when transactions carried out by the same user cannot be linked. An anonymous credential system is of significant practical relevance because it is the best means of providing privacy for users.
An Application of Bayesian classification to Interval Encoded Temporal mining with prioritized items
Venue: arXiv cs.DB 2009
Year: 2009

In real life, media information has time attributes either implicitly or explicitly known as temporal data. This paper investigates the usefulness of applying Bayesian classification to an interval encoded temporal database with prioritized items. The proposed method performs temporal mining by encoding the database with weighted items which prioritizes the items according to their importance from the user perspective. Naive Bayesian classification helps in making the resulting temporal rules more effective. The proposed priority based temporal mining (PBTM) method added with classification aids in solving problems in a well informed and systematic manner. The experimental results are obtained from the complaints database of the telecommunications system, which shows the feasibility of this method of classification based temporal mining.
Ethernet Networks: Current Trends and Tools
Venue: arXiv cs.NI 2009
Year: 2009

Ethernet topology discovery has gained increasing interest in the recent years. This trend is motivated mostly by increasing number of carrier Ethernet networks as well as the size of these networks, and consequently the increasing sales of these networks. To manage these networks efficiently, detailed and accurate knowledge of their topology is needed. Knowledge of a network's entities and the physical connections between them can be useful in various prospective. Administrators can use topology information for network planning and fault detecting. Topology information can also be used during protocol and routing algorithm development, for performance prediction and as a basis for accurate network simulations. From a network security perspective, threat detection, network monitoring, network access control and forensic investigations can benefit from accurate network topology information. In this paper, we analyze market trends and investigate current tools available for both research and commercial purposes.
Outage Regions and Optimal Power Allocation for Wireless Relay Networks
Venue: arXiv cs.IT 2009
Year: 2009

We study outage regions for energy-constrained multi-hop and adaptive multi-route networks with an arbitrary number of relay nodes. Optimal power allocation strategies in the sense that outage probability is minimized are derived depending on the distances between the transmit nodes. We further investigate the rate gain of adaptive multi-route and multi-hop over direct transmission. It is shown that a combined strategy of direct transmission and adaptive multi-route outperforms multi-hop for all values of rate R. It can be stated that cooperation strategies are beneficial for low-rate systems where the main goal is a very low outage probability of the network. As the rate is increased, direct transmission becomes more and more attractive.
A New Scaling Law on Throughput and Delay Performance of Wireless Mobile Relay Networks over Parallel Fading Channels
Venue: arXiv cs.IT 2009
Year: 2009

In this paper, utilizing the relay buffers, we propose an opportunistic decode-wait-and-forward relay scheme for a point-to-point communication system with a half-duplexing relay network to better exploit the time diversity and relay mobility. For instance, we analyze the asymptotic throughput-delay tradeoffs in a dense relay network for two scenarios: (1) fixed relays with \textit{microscopic fading} channels (multipath channels), and (2) mobile relays with \textit{macroscopic fading} channels (path loss). In the first scenario, the proposed scheme can better exploit the \textit{multi-relay diversity} in the sense that with $K$ fixed relays and a cost of $\mathcal{O}(K)$ average end-to-end packet delay, it could achieve the same optimal asymptotic average throughput as the existing designs (such as regular decode-and-forward relay schemes) with $K^2$ fixed relays. In the second scenario, the proposed scheme achieves the maximum throughput of $Θ(\log K)$ at a cost of $\mathcal{O}(K/q)$ average end-to-end packet delay, where $0<q\leq {1/2}$ measures the speed of relays' mobility. This system throughput is unattainable for the existing designs with low relay mobility, the proposed relay scheme can exploit the relays' mobility more efficiently.
Topological design of minimum cost survivable computer communication networks, Bipartite Graph Method
Venue: arXiv cs.NI 2009
Year: 2009

A good computer network is hard to disrupt. It is desired that the computer communication network remains connected even when some of the links or nodes fail. Since the communication links are expensive, one wants to achieve these goals with fewer links. The computer communication network is fault tolerant if it has alternative paths between vertices, the more disjoint paths, the better is the survivability. This paper presents a method for generating k-connected computer communication network with optimal number of links using bipartite graph concept.
Study of Proposed Methods for Improving TCP Performance Over Wireless Links
Venue: arXiv cs.NI 2009
Year: 2009

TCP is designed for networks with assumption that major losses occur only due to congestion of network traffic. On a wireless network TCP misinterprets the transmission losses due to bit errors and handoffs as losses caused by congestion, and triggers congestion control mechanisms. Because of its end to end delivery model, congestion handling and avoidance mechanisms, TCP has been widely accepted as Transport layer protocol for internetworks. Extension of Internetworks over wireless links is inevitable with the spread of ubiquitous computing and mobile communications. This paper presents study of different mechanisms proposed to extend Transport Control Protocol and other alternate solutions to enhance end to end performance over lossy wireless links. The paper studies details of different design choices proposed and their technical advantages and disadvantages. Finally, an analysis and proposal for best choice of proposed schemes are made for wireless networks.
On the Running Time of the Shortest Programs
Venue: arXiv cs.CC 2009
Year: 2009

The Kolmogorov complexity of the word w is equal to the length of the shortest concatenation of program Z and its input x with which the word w is computed by the universal turing machine U. The question introduced in this paper is the following: How long do the shortest programs run for?
STBCs with Reduced Sphere Decoding Complexity for Two-User MIMO-MAC
Venue: arXiv cs.IT 2009
Year: 2009

In this paper, Space-Time Block Codes (STBCs) with reduced Sphere Decoding Complexity (SDC) are constructed for two-user Multiple-Input Multiple-Output (MIMO) fading multiple access channels. In this set-up, both the users employ identical STBCs and the destination performs sphere decoding for the symbols of the two users. First, we identify the positions of the zeros in the $\textbf{R}$ matrix arising out of the Q-R decomposition of the lattice generator such that (i) the worst case SDC (WSDC) and (ii) the average SDC (ASDC) are reduced. Then, a set of necessary and sufficient conditions on the lattice generator is provided such that the $\textbf{R}$ matrix has zeros at the identified positions. Subsequently, explicit constructions of STBCs which results in the reduced ASDC are presented. The rate (in complex symbols per channel use) of the proposed designs is at most $2/N_{t}$ where $N_{t}$ denotes the number of transmit antennas for each user. We also show that the class of STBCs from complex orthogonal designs (other than the Alamouti design) reduce the WSDC but not the ASDC.
The Lookup Technique to Replace Nested-IF Formulas in Spreadsheet Programming
Venue: arXiv cs.SE 2009
Year: 2009

Spreadsheet programmers often implement contingent logic using a nested-IF formula even though this technique is difficult to test and audit and is believed to be risky. We interpret the programming of contingent logic in spreadsheets in the context of traditional computer programming. We investigate the "lookup technique" as an alternative to nested-IF formulas, describe its benefits for testing and auditing, and define its limitations. The lookup technique employs four distinct principles: 1) make logical tests visible; 2) make outcomes visible; 3) make logical structure visible; and 4) replace a multi-function nested-IF formula with a single-function lookup formula. It can be used only for certain simple contingent logic. We describe how the principles can be applied in more complex situations, and suggest avenues for further research.
Milestones for Teaching the Spreadsheet Program
Venue: arXiv cs.HC 2009
Year: 2009

There are different manners of teaching a spreadsheet program. In any case, it is intended that the teacher settles the objectives of the course and adapts them to the particular audience he/she has to deal with. This paper aims at providing any teacher whatever his/her specific objectives and his/her audience with elements to help him/her building a course. It focuses mainly on two important issues: 1 - select in all that may be said about such complex tools, what is prior to know and to teach, i.e. what leads to autonomy in using but also to autonomy in learning (because everything cannot be taught) and 2 - show how concepts are closely related to good formatting considerations. A method based on the "invariants of information processing" is outlined, partially illustrated and an implementation is described throughout a course designed for students preparing a master in Education Sciences.
Adaptive Training for Correlated Fading Channels with Feedback
Venue: arXiv cs.IT 2009
Year: 2009

We consider data transmission through a time-selective, correlated (first-order Markov) Rayleigh fading channel subject to an average power constraint. The channel is estimated at the receiver with a pilot signal, and the estimate is fed back to the transmitter. The estimate is used for coherent demodulation, and to adapt the data and pilot powers. We explicitly determine the optimal pilot and data power control policies in a continuous-time limit where the channel state evolves as an Ornstein-Uhlenbeck diffusion process, and is estimated by a Kalman filter at the receiver. The optimal pilot policy switches between zero and the maximum (peak-constrained) value (``bang-bang'' control), and approximates the optimal discrete-time policy at low Signal-to-Noise Ratios (equivalently, large bandwidths). The switching boundary is defined in terms of the system state (estimated channel mean and associated error variance), and can be explicitly computed. Under the optimal policy, the transmitter conserves power by decreasing the training power when the channel is faded, thereby increasing the data rate. Numerical results show a significant increase in achievable rate due to the adaptive training scheme with feedback, relative to constant (non-adaptive) training, which does not require feedback. The gain is more pronounced at relatively low SNRs and with fast fading. Results are further verified through Monte Carlo simulations.
Training Process Reduction Based On Potential Weights Linear Analysis To Accelarate Back Propagation Network
Venue: arXiv cs.NE 2009
Year: 2009

Learning is the important property of Back Propagation Network (BPN) and finding the suitable weights and thresholds during training in order to improve training time as well as achieve high accuracy. Currently, data pre-processing such as dimension reduction input values and pre-training are the contributing factors in developing efficient techniques for reducing training time with high accuracy and initialization of the weights is the important issue which is random and creates paradox, and leads to low accuracy with high training time. One good data preprocessing technique for accelerating BPN classification is dimension reduction technique but it has problem of missing data. In this paper, we study current pre-training techniques and new preprocessing technique called Potential Weight Linear Analysis (PWLA) which combines normalization, dimension reduction input values and pre-training. In PWLA, the first data preprocessing is performed for generating normalized input values and then applying them by pre-training technique in order to obtain the potential weights. After these phases, dimension of input values matrix will be reduced by using real potential weights. For experiment results XOR problem and three datasets, which are SPECT Heart, SPECTF Heart and Liver disorders (BUPA) will be evaluated. Our results, however, will show that the new technique of PWLA will change BPN to new Supervised Multi Layer Feed Forward Neural Network (SMFFNN) model with high accuracy in one epoch without training cycle. Also PWLA will be able to have power of non linear supervised and unsupervised dimension reduction property for applying by other supervised multi layer feed forward neural network model in future work.
Reducing the Risk of Spreadsheet Usage - a Case Study
Venue: arXiv cs.HC 2009
Year: 2009

The frequency with which spreadsheets are used and the associated risk is well known. Many tools and techniques have been developed which help reduce risks associate with creating and maintaining spreadsheet. However, little consideration has been given to reducing the risks of routine usage by the "consumers" - for example when entering and editing data. EASA's solution, available commercially, ensures that any routine process involving spreadsheets can be executed rapidly and without errors by the end-users, often with a significant reduction in manual effort. Specifically, the technology enables the rapid creation and deployment of web-based applications, connected to one or more centralized spreadsheets; this ensures version control, easy and error free usage, and security of intellectual property contained in spreadsheets.
Improved Sparsity Thresholds Through Dictionary Splitting
Venue: arXiv cs.IT 2009
Year: 2009

Known sparsity thresholds for basis pursuit to deliver the maximally sparse solution of the compressed sensing recovery problem typically depend on the dictionary's coherence. While the coherence is easy to compute, it can lead to rather pessimistic thresholds as it captures only limited information about the dictionary. In this paper, we show that viewing the dictionary as the concatenation of two general sub-dictionaries leads to provably better sparsity thresholds--that are explicit in the coherence parameters of the dictionary and of the individual sub-dictionaries. Equivalently, our results can be interpreted as sparsity thresholds for dictionaries that are unions of two general (i.e., not necessarily orthonormal) sub-dictionaries.
Interference Mitigation Through Limited Receiver Cooperation: Symmetric Case
Venue: arXiv cs.IT 2009
Year: 2009

Interference is a major issue that limits the performance in wireless networks, and cooperation among receivers can help mitigate interference by forming distributed MIMO systems. The rate at which receivers cooperate, however, is limited in most scenarios. How much interference can one bit of receiver cooperation mitigate? In this paper, we study the two-user Gaussian interference channel with conferencing decoders to answer this question in a simple setting. We characterize the fundamental gain from cooperation: at high SNR, when INR is below 50% of SNR in dB scale, one-bit cooperation per direction buys roughly one-bit gain per user until full receiver cooperation performance is reached, while when INR is between 67% and 200% of SNR in dB scale, one-bit cooperation per direction buys roughly half-bit gain per user. The conclusion is drawn based on the approximate characterization of the symmetric capacity in the symmetric set-up. We propose strategies achieving the symmetric capacity universally to within 3 bits. The strategy consists of two parts: (1) the transmission scheme, where superposition encoding with a simple power split is employed, and (2) the cooperative protocol, where quantize-binning is used for relaying.
Predictive Blacklisting as an Implicit Recommendation System
Venue: arXiv cs.NI 2009
Year: 2009

A widely used defense practice against malicious traffic on the Internet is through blacklists: lists of prolific attack sources are compiled and shared. The goal of blacklists is to predict and block future attack sources. Existing blacklisting techniques have focused on the most prolific attack sources and, more recently, on collaborative blacklisting. In this paper, we formulate the problem of forecasting attack sources (also referred to as predictive blacklisting) based on shared attack logs as an implicit recommendation system. We compare the performance of existing approaches against the upper bound for prediction, and we demonstrate that there is much room for improvement. Inspired by the recent Netflix competition, we propose a multi-level prediction model that is adjusted and tuned specifically for the attack forecasting problem. Our model captures and combines various factors, namely: attacker-victim history (using time-series) and attackers and/or victims interactions (using neighborhood models). We evaluate our combined method on one month of logs from Dshield.org and demonstrate that it improves significantly the state-of-the-art.
Quotient complexity of ideal languages
Venue: arXiv cs.FL 2009
Year: 2009

We study the state complexity of regular operations in the class of ideal languages. A language L over an alphabet Sigma is a right (left) ideal if it satisfies L = L Sigma* (L = Sigma* L). It is a two-sided ideal if L = Sigma* L Sigma *, and an all-sided ideal if it is the shuffle of Sigma* with L. We prefer the term "quotient complexity" instead of "state complexity", and we use derivatives to calculate upper bounds on quotient complexity, whenever it is convenient. We find tight upper bounds on the quotient complexity of each type of ideal language in terms of the complexity of an arbitrary generator and of its minimal generator, the complexity of the minimal generator, and also on the operations union, intersection, set difference, symmetric difference, concatenation, star and reversal of ideal languages.